A Brief Overview of Big Data Technology, Applications & Best Practices

 

In this article, our experts will provide you with a brief overview of Big Data Technology, applications, and best practices.

As the name suggests, big data is a collection of data that is too large or complex to be processed by standard applications.

A large number of rows in your data will provide greater statistical power, however, a larger number of columns or attributes can make your data more likely to contain fake matches.

Datacenter challenges include taking data, storing it, analyzing it, searching for it, sharing it, transferring it, visualizing it, querying it, updating it, and ensuring that information is private.

Several key concepts are associated with it, including variety, volume, and velocity.

In later years, credibility and value have also been associated with big data.

Three V’s of Big Data

Volume: Team members collect information from a wide range of resources, such as social media, business transactions and sensors.

Velocity: With Velocity data pours in at an unusual speed and needs to be treated immediately.

Variety: Data can be found in all types of formats in Variety, from structured, numeric data in traditional databases to unstructured text documents, email, video, audio, stock ticker data, and financial transactions.

Variability: A periodic tip can dramatically change data flows depending on the speed and type of data being expanded.

Have you ever seen something trending on social media? With unorganized data, we need to be sure to check seasonal and event-triggered peak data loads regularly.

Complexity: In today's world, there is a wide diversity of data sources, making linking, matching, cleaning, and transforming data across systems very difficult.

Technologies

Here are some Big Data technologies you should know:

1. Apache Spark

2. Hadoop Eco-System

3. R

4. Cloud Data Flow

5. NoSQL Databases

Applications

The following applications are available:

1. Government

2. Healthcare

3. Media

4. Education

5. Insurance

Best Practices

Best Practices for Big Data:

1. Serving specific business goals with big data

2. A Center of Excellence can optimize knowledge transfer

3. Lack of skills and confidence in Standards and Governance    

4. Top Payoff Is Arranging Unorganized with Organized Data

5. Adopt an operating model aligned with cloud computing

6. Create a Discovery Lab to Meet Your Goals

Conclusion

A major benefit of Big Data technology is that it is used to collect large quantities of data, which is difficult for common data-processing applications to handle well. Ask our experts for help if you need Big Data Assignment Help.